Top-down causation and emergence: some comments on mechanisms

The place of the social in psychiatry: from structural determinants to the ecology of mind

PURPOSE

Social psychiatry considers the ways in which mental disorders are shaped by particular social environments. This paper outlines a cultural-ecosocial approach that emphasizes the ways in which cultural meaning and practices mediate the effects of the social determinants of mental health on the mechanisms of illness, disorder, and disease.

METHODS

Selective review of literature and conceptual synthesis.

RESULTS

"The social" in psychiatry stands for the structures and dynamics of groups of people interacting on multiple scales from the intimate sphere of couple and family to neighbourhoods, communities, societies, nations, and transnational or global networks. These interactions create social contexts, niches, forms of belonging, identities, institutions, and larger systems that influence the causes, expression, course, and outcome of mental disorders. Characterizing these systems requires theory that considers the ways in which social systems constitute dynamical systems that configure material, energetic, and informational flows that give rise to human experience. Unpacking the health consequences of these local and extended systems requires an interdisciplinary approach that considers: (1) the social psychological, psychophysiological, and sociophysiological processes that mediate the impact of the environment on body, mind, and person; (2) the interactional dynamics of social systems that give rise to structural adversity and inequity as well as resilience; and (3) the recursive effects of self-understanding, agency and subjectivity.

CONCLUSIONS

In the cultural-ecosocial view, "the social" is shorthand for interactional processes that constitute material and symbolic structures that provide cultural affordances, constraints, and challenges as well as resources for healing, recovery, and adaptation.

How Physical Information Underlies Causation and the Emergence of Systems at all Biological Levels

To bring clarity, the term 'information' is resolved into three distinct meanings: physical pattern, statistical relations and knowledge about things. In parallel, three kinds of 'causation' are resolved: the action of physical force constrained by physical pattern (efficient cause), cybernetic (formal cause) and statistical inference. Cybernetic causation is an expression of fundamental (necessary) logical relations, statistical inference is phenomenological, but physical information and causation are proposed as what actually happens in the physical world. Examples of the latter are given to illustrate the underlying material dynamics in a range of biological systems from the appearance of 'synergistic information' among multiple variables (mainly in neuroscience); positional information in multicellular development; and the organisational structure of ecological communities, especially incorporating niche construction theory. A rigorous treatment of multi-level causation is provided as well as an explanation of the causal power of non-physical information structure, especially of interaction networks. The focus on physical information as particular pattern, echoing the insights of Howard Pattee, provides a more physically grounded view of emergence, downward causation and the concept of 'closure to efficient causation', all now prevalent in the organisational approach to biology.

Beyond Mechanism-Extending Our Concepts of Causation in Neuroscience

In neuroscience, the search for the causes of behaviour is often just taken to be the search for neural mechanisms. This view typically involves three forms of causal reduction: first, from the ontological level of cognitive processes to that of neural mechanisms; second, from the activity of the whole brain to that of isolated parts; and third, from a consideration of temporally extended, historical processes to a focus on synchronic states. While modern neuroscience has made impressive progress in identifying synchronic neural mechanisms, providing unprecedented real-time control of behaviour, we contend that this does not amount to a full causal explanation. In particular, there is an attendant danger of eliminating the cognitive from our explanatory framework, and even eliminating the organism itself. To fully understand the causes of behaviour, we need to understand not just what happens when different neurons are activated, but why those things happen. In this paper, we introduce a range of well-developed, non-reductive, and temporally extended notions of causality from philosophy, which neuroscientists may be able to draw on in order to build more complete causal explanations of behaviour. These include concepts of criterial causation, triggering versus structuring causes, constraints, macroscopic causation, historicity, and semantic causation-all of which, we argue, can be used to undergird a naturalistic understanding of mental causation and agent causation. These concepts can, collectively, help bring cognition and the organism itself back into the picture, as a causal agent unto itself, while still grounding causation in respectable scientific terms.

What We Mean By 'Values in Healthcare': The Importance of Reaching a Consensus

The concept of 'values' in healthcare is widely debated, with no universal definition despite its central role in health system reform. This paper does not seek to define value narrowly but instead aims to stimulate a generative discussion among stakeholders. Using a systems-thinking framework, we explore four key perspectives: the subjective and value-laden nature of 'value,' the influence of financial interests, the role of personal values in shaping care delivery, and the potential for a shared human-centred value framework. By highlighting the diverse and often conflicting interpretations of value, we encourage an inclusive dialogue to guide the development of health systems that are equitable, patient-centred, and sustainable, benefiting individual stakeholders and society at large.

Agency

Agency is action aimed at goals selected by an agent. A deterministic world view leaves scant room for agency. To reconcile the arguments, we represent action as nested control systems, ranging from clearly deterministic to clearly volitional. Negative feedback minimizes deviations from setpoints (goals). Goals are determined by higher modules in a hierarchy of systems, ranging from gamma-efferent spindles through reflexes to operant responses; these last, and the larger system that contains them, called the Self, comprise volitional agents. When operants become habitual they descend to closed teleonomic systems-automaticity. Change in emotional states, and unpredicted changes in the context-raise them back to full volitional systems. At the highest level is the Self-the brain's model of the agent. When aroused out of open teleonomic functioning, it must reconsider means and ends. It does so by simulating action plans, using the same neural systems it uses to effect them. The simulated stimuli and responses are conscious, approximating their perceptions as experienced in real time; this verisimilitude gives them their hedonic value. Positive feedback plays a key role in these complex adaptive systems, as it focuses and holds attention on the most salient percepts and goals, permitting the self-organization of action plans. The Self is not a separate entity, but a colloquy of command modules wearing the avatar of the agent. This system is put into correspondence with Grossberg's Adaptive Resonance Theory. Free will and determinism emerge not as binary opposites, but the modulating inputs to a spectrum of systems.

Exploring the Role of Genetic and Environmental Features in Colorectal Cancer Development: An Agent-Based Approach

The complexity of issues in cancer research has led to the introduction of powerful computational tools to help experimental in vivo and in vitro methods. These tools, which typically focus on studying cell behavior and dynamic cell populations, range from systems of differential equations that are solved numerically to lattice models and agent-based simulations. In particular, agent-based models (ABMs) are increasingly used due to their ability to incorporate multi-scale features, ranging from the individual to the population level. This approach allows for the combination of statistically aggregated assumptions with individual heterogeneity. In this work, we present an ABM that simulates tumor progression in a colonic crypt, to provide an experimental in silico environment for testing results achieved in traditional laboratory research and developing alternative scenarios of tumor development. The model also allows some speculations about causal relationships in biologically inspired systems.

Systemic failures in nursing home care-A scoping study

Nursing homes (also referred to as residential aged care facilities, or long-term care facilities) cater for older people on a respite or long-term basis for those who are no longer able to live independently at home. Globally the sector struggles to meet societal expectations since it is torn between three competing agendas-meeting the needs of residents, meeting the demands of regulators, and meeting the financial imperatives of nursing home proprietors. Competing demands indicate that the system lacks a clear understanding of its purpose-without a clearly understood purpose any system will become dysfunctional overall and across all its levels of organisation. This scoping study aims to summarise and synthesise what is already known about the systemic function and failures in the nursing home system, and the impact this has on the wider health and aged care system.

METHOD

MEDLINE, EMBASE, PSYCHINFO, CINAHL and SCOPUS were searched using the terms: (nursing home care OR residential aged care OR nursing home) AND (organisational failure OR institutional failure OR systemic failure), limited to English language articles, including all years up to the end of February 2021. In addition, we used snowballing of article references and Google searches of the grey literature. System-focused articles were defined as those that explored how an issue at one system level impacted other system levels, or how an issue impacted at least two different agents at the same system level.

RESULT

Thirty-eight articles addressed systemic issues as defined in four different contexts: United States (14), Canada (2), Australia (11) and European countries (11). Only four studies reported whole-of-system findings, whereas the remaining 34 more narrowly addressed systemic features of specific nursing home issues. The thematic analysis identified 29 key systemic issues across five system layers which consistently appear across every country/health system context. The negative outcomes of these systemic failings include: high rates of regulatory reprimands for unacceptable or unsafe practices; dissatisfaction in care experiences on the part of residents, families, and care staff-including a fear of being sent to a nursing home; and the perception amongst staff that nursing homes are not preferred places to work.

CONCLUSIONS

The key issues affecting nursing home residents, and the care home sector more generally, are systemic in nature arising from two key issues: first, the lack of shared agreement on the care home system's purpose; and second, the lack of clear governance and accountability frameworks for system regulation and performance at a national level. Addressing these two key issues must be the starting point for any 'real' nursing home system redesign that can achieve a seamlessly integrated system that delivers the outcomes nursing home residents and their families expect. 'Systems thinking' is required to simultaneously improve care quality and outcomes for residents, strengthen regulation and accountability, and enable financial viability.

Complex adaptive organisations: How three-dimensional visualisations can help to understand their structures and behaviours

Many organisations struggle to achieve their true potential. In part it is a problem of organisational design, which is an outcome of a particularly common-command and control-leadership philosophy. The traditional linear hierarchical structure of organisations suggests that all knowledge and power concentrates at the top organisational layer, and that people in the lower layers need to be told what to do and when. These arrangements disempower people at the lower level, preventing them from providing the necessary feedback to pre-emptively address emerging concerns. Systems and complexity thinking provide different ways of understanding organisations and their complex adaptive behaviours. In this paper, we first describe the key characteristics of complex adaptive organisations-their structure and dynamic behaviours-and then propose a three-dimensional visualisation of a complex adaptive organisation that allows its members to clearly see and appreciate its interdependencies.

Assembly theory explains and quantifies selection and evolution

Scientists have grappled with reconciling biological evolution1,2 with the immutable laws of the Universe defined by physics. These laws underpin life's origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Evolutionary theory explains why some things exist and others do not through the lens of selection. To comprehend how diverse, open-ended forms can emerge from physics without an inherent design blueprint, a new approach to understanding and quantifying selection is necessary3-5. We present assembly theory (AT) as a framework that does not alter the laws of physics, but redefines the concept of an 'object' on which these laws act. AT conceptualizes objects not as point particles, but as entities defined by their possible formation histories. This allows objects to show evidence of selection, within well-defined boundaries of individuals or selected units. We introduce a measure called assembly (A), capturing the degree of causation required to produce a given ensemble of objects. This approach enables us to incorporate novelty generation and selection into the physics of complex objects. It explains how these objects can be characterized through a forward dynamical process considering their assembly. By reimagining the concept of matter within assembly spaces, AT provides a powerful interface between physics and biology. It discloses a new aspect of physics emerging at the chemical scale, whereby history and causal contingency influence what exists.

Efficient, Formal, Material, and Final Causes in Biology and Technology

This paper considers how a classification of causal effects as comprising efficient, formal, material, and final causation can provide a useful understanding of how emergence takes place in biology and technology, with formal, material, and final causation all including cases of downward causation; they each occur in both synchronic and diachronic forms. Taken together, they underlie why all emergent levels in the hierarchy of emergence have causal powers (which is Noble's principle of biological relativity) and so why causal closure only occurs when the upwards and downwards interactions between all emergent levels are taken into account, contra to claims that some underlying physics level is by itself causality complete. A key feature is that stochasticity at the molecular level plays an important role in enabling agency to emerge, underlying the possibility of final causation occurring in these contexts.

Is information the other face of causation in biological systems?

Is information the other face of causation? This issue cannot be clarified without discussing how these both are related to physical laws, logic, computation, networks, bio-signaling, and the mind-body problem. The relation between information and causation is also intrinsically linked to many other concepts in complex systems theory such as emergence, self-organization, synergy, criticality, and hierarchy, which in turn involve various notions such as observer-dependence, dimensionality reduction, and especially downward causation. A canonical example proposed for downward causation is the collective behavior of the whole system at a macroscale that may affect the behavior of each its member at a microscale. In neuroscience, downward causation is suggested as a strong candidate to account for mental causation (free will). However, this would be possible only on the condition that information might have causal power. After introducing the Causal Equivalence Principle expanding the relativity principle for coarse-grained and fine-grained linear causal chains, and a set-theoretical definition of multiscale nested hierarchy composed of modular ⊂-chains, it is shown that downward causation can be spurious. It emerges only in the eyes of an observer, though, due to information that could not be obtained by "looking" exclusively at the behavior of a system at a microscale. On the other hand, since biological systems are hierarchically organized, this information gain is indicative of how information can be a function of scale in these systems and a prerequisite for scale-dependent emergence of cognition and consciousness in neural networks.

Disruption of polyhomeotic polymerization decreases nucleosome occupancy and alters genome accessibility

Chromatin attains its three-dimensional (3D) conformation by establishing contacts between different noncontiguous regions. Sterile Alpha Motif (SAM)-mediated polymerization of the polyhomeotic (PH) protein regulates subnuclear clustering of Polycomb Repressive Complex 1 (PRC1) and chromatin topology. The mutations that perturb the ability of the PH to polymerize, disrupt long-range chromatin contacts, alter Hox gene expression, and lead to developmental defects. To understand the underlying mechanism, we combined the experiments and theory to investigate the effect of this SAM domain mutation on nucleosome occupancy and accessibility on a genome wide scale. Our data show that disruption of PH polymerization because of SAM domain mutation decreases nucleosome occupancy and alters accessibility. Polymer simulations investigating the interplay between distant chromatin contacts and nucleosome occupancy, both of which are regulated by PH polymerization, suggest that nucleosome density increases when contacts between different regions of chromatin are established. Taken together, it appears that SAM domain-mediated PH polymerization biomechanically regulates the organization of chromatin at multiple scales from nucleosomes to chromosomes and we suggest that higher order organization can have a top-down causation effect on nucleosome occupancy.

Perspectives of (/memorandum for) systems thinking on COVID-19 pandemic and pathology

Is data-driven analysis sufficient for understanding the COVID-19 pandemic and for justifying public health regulations? In this paper, we argue that such analysis is insufficient. Rather what is needed is the identification and implementation of over-arching hypothesis-related and/or theory-based rationales to conduct effective SARS-CoV2/COVID-19 (Corona) research. To that end, we analyse and compare several published recommendations for conceptual and methodological frameworks in medical research (e.g., public health, preventive medicine and health promotion) to current research approaches in medical Corona research. Although there were several efforts published in the literature to develop integrative conceptual frameworks before the COVID-19 pandemic, such as social ecology for public health issues and systems thinking in health care, only a few attempts to utilize these concepts can be found in medical Corona research. For this reason, we propose nested and integrative systemic modelling approaches to understand Corona pandemic and Corona pathology. We conclude that institutional efforts for knowledge integration and systemic thinking, but also for integrated science, are urgently needed to avoid or mitigate future pandemics and to resolve infection pathology.

A new species of Euclymene (Maldanidae, Annelida) from Brazil, with new combinations, and phylogenetic implications for Euclymeninae

Maldanids are tube-building polychaetes, known as bamboo-worms; inhabit diverse marine regions throughout the world. The subfamily Euclymeninae was proposed to include forms with anal and cephalic plates, a funnel-shaped pygidium, and a terminal anus. Euclymene, the type genus of Euclymeninae, has about 18 valid species. Euclymene vidali sp. nov. is defined and members of the species described from Northeastern Brazil. Members of this species have 23 chaetigers, and one pre-pygidial achaetous segment; nuchal grooves extend through three quarters of the cephalic plate, and there is one acicular spine with a denticulate tip. Euclymene africana, and E. watsoni, are here recognized, respectively, as Isocirrus africana comb. nov., and I. watsoni comb. nov. Three monotypic genera are invalid: Macroclymenella, Eupraxillella, and Pseudoclyemene; their species should be recognized as Clymenella stewartensis com. nov., Praxillella antarctica com. nov., and Praxillela quadrilobata com. nov., respectively. An identification key and a comparative table for all species of Euclymene are provided. A comparative table for all genera of Euclymeninae is also furnished. The paraphyletic status of Euclymene and Euclymeninae is discussed. The taxon Maldanoplaca is not code compliant and should only be regarded as an informal name.

Contingencies of Violent Radicalization: The Terror Contagion Simulation

This paper builds confidence in the terror contagion hypothesis that violent radicalization leading to predatory mass violence operates as a system. Within this system, the contingent values of key root causes create channels within which violent ideologies and terrorism emerge. We built a system dynamics simulation model capable of replicating historical reference modes and sophisticated enough to test the contingent values of these propositions. Of 16 propositions, we identified six root-cause propositions that must simultaneously exist, act in concert and explain the dynamics of their interaction which generate a terror contagion. Other propositions can strengthen or weaken an existing contagion but not eliminate it. We use an experiment to demonstrate how changing the contingent values of these propositions creates downward channels. This experiment helps reconcile the swarm vs. fishermen debate over the true root causes of violent radicalization. Within these channels, the contingent values can favor swarm or fishermen manifestations. The simulation and experimentation results enable the future development of the terror contagion hypothesis, provide a testing environment for research on violent radicalization, and provide a pathway to policy development in the combating of terrorism that arises from violent radicalization.

Universal health care - A matter of design and agency?

Universal health care (UHC) is primarily a financing concern, whereas primary health care (PHC) is primarily concerned with providing the right care at the right time to achieve the best possible health outcomes for individuals and communities. A recent call for contributions by the WHO emphasized that UHC can only be achieved through PHC, and that to achieve this goal will require the strengthening of the three pillars of PHC - (a) enabling primary care and public health to integrate health services, (b) empowering people and communities to create healthy living conditions, and (c) integrating multisectoral policy decisions to ensure UHC that achieves the goal of "health for all." "Pillars" - as a static metaphor - sends the wrong signal to the research and policy-making community. It, in fact, contradicts the WHO's own view, namely that there is "the need to strengthen comprehensive primary health care systems based on local priorities, needs and contexts … [that are] co-developed by people who are engaged in their own health." What we really need to develop PHC as the basis to achieve the goal of UHC is a dynamic agency to drive a "system-as-a-whole framework" that simultaneously takes into account finance, individual, and local needs. Health systems are socially constructed organizational systems that are "functionally layered" in a hierarchical fashion - governments and/or funders at the top-level not only promote the goals of the system (policies) but also constrain the system (rules, regulations, resources) in its ability to deliver. Hence, there is a need to focus on two key system features - political leadership and dynamic bottom-up agency that maintains everyone's focus on the goal to be achieved, and a limitation of system constraints so that communities can shape best adapted primary care services that truly meet the needs of their individuals, families, and community.

Improving quality in a complex primary care system-An example of refugee care and literature review

RATIONALE, AIMS AND OBJECTIVES

Applying traditional industrial quality improvement (QI) methodologies to primary care is often inappropriate because primary care and its relationship to the healthcare macrosystem has many features of a complex adaptive system (CAS) that is particularly responsive to bottom-up rather than top-down management approaches. We report on a demonstration case study of improvements made in the Family Health Center (FHC) of the JPS Health Network in a refugee patient population that illustrate features of QI in a CAS framework as opposed to a traditional QI approach.

METHODS

We report on changes in health system utilization by new refugee patients of the FHC from 2016 to 2017. We review the literature and summarize relevant theoretical understandings of quality management in complex adaptive systems as it applies to this case example.

RESULTS

Applying CAS principles in the FHC, utilization of the Emergency Department and Urgent Care Center by newly arrived refugee patients before their first clinic visit was reduced by more than half (total visits decreased from 31%-14% of the refugee patients). Our review of the literature demonstrates that traditional algorithmic top-down QI processes are most often unsuccessful in improving even a few single-disease metrics, and increases clinician burnout and penalizes clinicians who care for vulnerable patients. Improvement in a CAS occurs when front-line clinicians identify care gaps and are given the flexibility to learn and self-organize to enable new care processes to emerge, which are created from bottom-up leadership that utilize existing interdependencies and interact with the top levels of the organization through intelligent top-down causation. We give examples of early adapters who are better applying the principles of CAS change to their QI efforts.

CONCLUSIONS

Meaningful improvement in primary care is more likely achieved when the impetus to implement change shifts from top-down to bottom-up.

Multiple Routes to Animal Consciousness: Constrained Multiple Realizability Rather Than Modest Identity Theory

The multiple realizability thesis (MRT) is an important philosophical and psychological concept. It says any mental state can be constructed by multiple realizability (MR), meaning in many distinct ways from different physical parts. The goal of our study is to find if the MRT applies to the mental state of consciousness among animals. Many things have been written about MRT but the ones most applicable to animal consciousness are by Shapiro in a 2004 book called The Mind Incarnate and by Polger and Shapiro in their 2016 work, The Multiple Realization Book. Standard, classical MRT has been around since 1967 and it says that a mental state can have very many different physical realizations, in a nearly unlimited manner. To the contrary, Shapiro's book reasoned that physical, physiological, and historical constraints force mental traits to evolve in just a few, limited directions, which is seen as convergent evolution of the associated neural traits in different animal lineages. This is his mental constraint thesis (MCT). We examined the evolution of consciousness in animals and found that it arose independently in just three animal clades-vertebrates, arthropods, and cephalopod mollusks-all of which share many consciousness-associated traits: elaborate sensory organs and brains, high capacity for memory, directed mobility, etc. These three constrained, convergently evolved routes to consciousness fit Shapiro's original MCT. More recently, Polger and Shapiro's book presented much the same thesis but changed its name from MCT to a "modest identity thesis." Furthermore, they argued against almost all the classically offered instances of MR in animal evolution, especially against the evidence of neural plasticity and the differently expanded cerebrums of mammals and birds. In contrast, we argue that some of these classical examples of MR are indeed valid and that Shapiro's original MCT correction of MRT is the better account of the evolution of consciousness in animal clades. And we still agree that constraints and convergence refute the standard, nearly unconstrained, MRT.

Who's who in Magelona: phylogenetic hypotheses under Magelonidae Cunningham & Ramage, 1888 (Annelida: Polychaeta)

Known as shovel head worms, members of Magelonidae comprise a group of polychaetes readily recognised by the uniquely shaped, dorso-ventrally flattened prostomium and paired ventro-laterally inserted papillated palps. The present study is the first published account of inferences of phylogenetic hypotheses within Magelonidae. Members of 72 species of Magelona and two species of Octomagelona were included, with outgroups including members of one species of Chaetopteridae and four of Spionidae. The phylogenetic inferences were performed to causally account for 176 characters distributed among 79 subjects, and produced 2,417,600 cladograms, each with 404 steps. A formal definition of Magelonidae is provided, represented by a composite phylogenetic hypothesis explaining seven synapomorphies: shovel-shaped prostomium, prostomial ridges, absence of nuchal organs, ventral insertion of palps and their papillation, presence of a burrowing organ, and unique body regionation. Octomagelona is synonymised with Magelona due to the latter being paraphyletic relative to the former. The consequence is that Magelonidae is monotypic, such that Magelona cannot be formally defined as associated with any phylogenetic hypotheses. As such, the latter name is an empirically empty placeholder, but because of the binomial name requirement mandated by the International Code of Zoological Nomenclature, the definition is identical to that of Magelonidae. Several key features for future descriptions are suggested: prostomial dimensions, presence/absence of prostomial horns, morphology of anterior lamellae, presence/absence of specialised chaetae, and lateral abdominal pouches. Additionally, great care must be taken to fully describe and illustrate all thoracic chaetigers in descriptions.

Constraints in Clinical Cardiology and Personalized Medicine: Interrelated Concepts in Clinical Cardiology

Systems biology is established as an integrative computational analysis methodology with practical and theoretical applications in clinical cardiology. The integration of genetic and molecular components of a disease produces interacting networks, modules and phenotypes with clinical applications in complex cardiovascular entities. With the holistic principle of systems biology, some of the features of complexity and natural progression of cardiac diseases are approached and explained. Two important interrelated holistic concepts of systems biology are described; the emerging field of personalized medicine and the constraint-based thinking with downward causation. Constraints in cardiovascular diseases embrace three scientific fields related to clinical cardiology: biological and medical constraints; constraints due to limitations of current technology; and constraints of general resources for better medical coverage. Systems healthcare and personalized medicine are connected to the related scientific fields of: ethics and legal status; data integration; taxonomic revisions; policy decisions; and organization of human genomic data.

The Quest for System-Theoretical Medicine in the COVID-19 Era

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum.

Health and Disease Are Dynamic Complex-Adaptive States Implications for Practice and Research

Interoception, the ability to convey one's overall physiological state, allows people to describe their health along an experiential continuum, from excellent, very good, good, fair to poor. Each health state reflects a distinct pattern of one's overall function. This assay provides a new frame of understanding health and disease as complex-adaptive system states of the person as-a-whole. It firstly describes how complex patterns can emerge from simple equations. It then discusses how clinical medicine in certain domains has started to explore the pattern characteristics resulting in the heterogeneity of disease, and how this better understanding has improved patient management. The experiential state of health can be surprising to the observer-some are in good health with disabling disease, others are in poor health without the evidence of any. The main part of the assay describes the underlying complexity principles that contribute to health, and synthesizes available evidence from various research perspectives to support the philosophic/theoretical proposition of the complex-adaptive nature of health. It shows how health states arise from complex-adaptive system dynamics amongst the variables of a hierarchically layered system comprising the domains of a person's macro-level external environment to his nano-level biological blueprint. The final part suggests that the frame of health as a dynamic complex-adaptive state defines a new paradigm, and outlines ways of translating these expanded understandings to clinical practice, future research, and health system design.

An organisational systems-biology view of viruses explains why they are not alive

Whether or not viruses are alive remains unsettled. Discoveries of giant viruses with translational genes and large genomes have kept the debate active. Here, a fresh approach is introduced, based on the organisational definition of life from within systems biology. It views living as a circular process of self-organisation and self-construction which is 'closed to efficient causation'. How information combines with force to fabricate and organise environmentally obtained materials, given an energy source, is here explained as a physical embodiment of informational constraint. Comparing a general virus replication cycle with Rosen's (M,R)-system shows it to be linear, rather than closed. Some viruses contribute considerable organisational information, but so far none is known to supply all required, nor the material nor energy necessary to complete their replication cycle. As a result, no known virus replication cycle is closed to efficient causation: unlike cellular obligate parasites, viruses do not match the causal structure of an (M,R)-system. Analysis based in identifying a Markov blanket in causal structure proved inconclusive, but using Integrated Information Theory on a Boolean representation, it was possible to show that the causal structure of a virocell is not different from that of the host cell.

The Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation

Evolution exploits the physics of non-neural bioelectricity to implement anatomical homeostasis: a process in which embryonic patterning, remodeling, and regeneration achieve invariant anatomical outcomes despite external interventions. Linear "developmental pathways" are often inadequate explanations for dynamic large-scale pattern regulation, even when they accurately capture relationships between molecular components. Biophysical and computational aspects of collective cell activity toward a target morphology reveal interesting aspects of causation in biology. This is critical not only for unraveling evolutionary and developmental events, but also for the design of effective strategies for biomedical intervention. Bioelectrical controls of growth and form, including stochastic behavior in such circuits, highlight the need for the formulation of nuanced views of pathways, drivers of system-level outcomes, and modularity, borrowing from concepts in related disciplines such as cybernetics, control theory, computational neuroscience, and information theory. This approach has numerous practical implications for basic research and for applications in regenerative medicine and synthetic bioengineering.

The Causal Closure of Physics in Real World Contexts

The causal closure of physics is usually discussed in a context free way. Here I discuss it in the context of engineering systems and biology, where strong emergence takes place due to a combination of upwards emergence and downwards causation (Ellis, Emergence in Solid State Physics and Biology, 2020, arXiv:2004.13591). Firstly, I show that causal closure is strictly limited in terms of spatial interactions because these are cases that are of necessity strongly interacting with the environment. Effective Spatial Closure holds ceteris parabus, and can be violated by Black Swan Events. Secondly, I show that causal closure in the hierarchy of emergence is a strictly interlevel affair, and in the cases of engineering and biology encompasses all levels from the social level to the particle physics level. However Effective Causal Closure can usefully be defined for a restricted set of levels, and one can experimentally determine Effective Theories that hold at each level. This does not however imply those effective theories are causally complete by themselves. In particular, the particle physics level is not causally complete by itself in the contexts of solid state physics (because of interlevel wave-particle duality), digital computers (where algorithms determine outcomes), or biology (because of time dependent constraints). Furthermore Inextricably Intertwined Levels occur in all these contexts.

Rethinking Causation for Data-intensive Biology: Constraints, Cancellations, and Quantized Organisms: Causality in complex organisms is sculpted by constraints rather than instigators, with outcomes perhaps better described by quantized patterns than rectilinear pathways

Complex organisms thwart the simple rectilinear causality paradigm of "necessary and sufficient," with its experimental strategy of "knock down and overexpress." This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include "eigenisms," organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed "sheets" rather than single control points.

The meaning-making mechanism(s) behind the eyes and between the ears

In this contribution, the following four questions are discussed: (i) where is meaning?; (ii) what is meaning?; (iii) what is the meaning of mechanism?; (iv) what are the mechanisms of meaning? I will argue that meanings are in the head. Meanings have multiple facets, but minimally one needs to make a distinction between single word meanings (lexical meaning) and the meanings of multi-word utterances. The latter ones cannot be retrieved from memory, but need to be constructed on the fly. A mechanistic account of the meaning-making mind requires an analysis at both a functional and a neural level, the reason being that these levels are causally interdependent. I will show that an analysis exclusively focusing on patterns of brain activation lacks explanatory power. Finally, I shall present an initial sketch of how the dynamic interaction between temporo-parietal areas and inferior frontal cortex might instantiate the interpretation of linguistic utterances in the context of a multimodal setting and ongoing discourse information. This article is part of the theme issue 'Towards mechanistic models of meaning composition'.

Dynamic Systems, Process and Development

In this article, I answer the questions from Witherington and Boom's introduction to this special issue in the form of an imaginary interview, led by David Boom, equally imaginary editor of The Processual Inquirer, an obscure but interesting journal that appears in imaginary physical print only, and which, as a consequence, has so far left no traces on the Internet….

Evidence-based medicine-Not a panacea for the problems of a complex adaptive world

The recent sacking of Peter Gøtzsche from the Cochrane Collaboration Board raised strong responses and highlights the neglected issue about priorities-maintaining the reputation of the organization or vigorously debating the merits of scientific approaches to find answers to complex problems? The Cochrane approach hales the randomized trial (RCT) as the gold standard research approach and affirms that meta-analysis provides the ultimate proof (or platinum standard) to settle contentious issues confronting the clinician. However, most published medical research is wrong, and critics coined the acronym GIGO (garbage in, garbage out) as a meme to highlight the risks of blind faith in the hyped-up procedures of the EBM movement. This paper firstly explores the differences between the prevailing scientific method arising from the linear cause-and-effect assumption and the complex adaptive systems science methods arising from observations that most phenomena emerge from nonlinearity in networked systems. Most medical conditions are characterized by necessary features that by themselves are not sufficient to explain their nature and behaviour. Such nonlinear phenomena require modelling approaches rather than linear statistical and/or meta-analysis approaches to be understood. These considerations also highlight that research is largely stuck at the data and information levels of understanding which fails clinicians who depend on knowledge-the synthesis of information-to apply in an adaptive way in the clinical encounter. Clinicians are constantly confronted with the linked challenges of doing things right and doing the right thing for their patients. EBM and Cochrane with their restrictive approaches are the antithesis to a practice of medicine that is responsive to constantly changing patient needs. As such, the EBM/Cochrane crisis opens a window of opportunity to re-examine the nature of health, illness and disease, and the nature of health care and its systems for the benefits of its professionals and their patients. We are at the cusp of a paradigmatic shift towards an understanding a praxis of health care that takes account of its complexities.

A proposed mechanism for mind-brain interaction using extended Bohmian quantum mechanics in Avicenna's monotheistic perspective

In quantum approaches to consciousness, the authors try to propose a model and mechanism for the mind-brain interaction using modern physics and some quantum concepts which do not exist in the classical physics. The independent effect of mind on the brain has been one of the challenging issues in the history of science and philosophy. In some recent mind-brain interaction models, the direct influence of mind on matter is either not accepted (as in Stapp's model) or not clear, and there have not been any clear mechanism for it (as in Penrose-Hameroff's model or in Eccles's model). In this manuscript we propose a model and mechanism for mind's effect on the matter using an extended Bohmian quantum mechanics and Avicenna's ideas. We show that mind and mental states can affect brain's activity without any violation of physical laws. This is a mathematical and descriptive model which shows the possibility of providing a causal model for mind's effect on matter. It is shown that this model guarantees the realistic philosophical constraints and respects the laws of nature. In addition, it is shown that it is in agreement with the Libet style experimental results and parapsychological data. To propose this model, we obtained a modified (non-unitary) Schrödinger equation via second quantization method which affects the particle through a modified quantum potential and a new term in the continuity equation. At the second quantized level, which is equivalent to quantum field theory level (QFT), we can use the path integral formalism of Feynman. We show that there are three methods to extend Bohmian QM via path integral formalism, which has different interpretations. By numerical simulation of trajectories in the two-slits experiment, we show their differences and choose one of these methods for our mind-brain model which can be the basis for explaining some phenomena which are not possible to explain in the standard Bohmian QM.

Better and fulfilling healthcare at lower costs: The need to manage health systems as complex adaptive systems

Rising healthcare costs are major concerns in most high-income countries. Yet, political measures to reduce costs have so far remained futile and have damaged the best interests of patients and citizen. We therefore explored the possibilities to analyze healthcare systems as a socially constructed complex adaptive system (CAS) and found that by their very nature such CAS tend not to respond as expected to top-down interventions. As CAS have emergent behaviors, the focus on their drivers - purpose, economy and behavioral norms - requires particular attention. First, the importance of understanding the purpose of health care as improvement of health and its experience has been emphasized by two recent complementary re-definitions of health and disease. The economic models underpinning today's healthcare - profit maximization - have shifted the focus away from its main purpose. Second, although economic considerations are important, they must serve and not dominate the provision of healthcare delivery. Third, expected health professionals' behavioral norms - to first consider the health and wellbeing of patients - have been codified in the universally accepted Declaration of Geneva 2017. Considering these three aspects it becomes clear that complex adaptive healthcare systems need mindful top-down/bottom-up leadership that supports the nature of innovation for health care driven by local needs. The systemic focus on improving people's health will then result in significant cost reductions.

Health and Disease-Emergent States Resulting From Adaptive Social and Biological Network Interactions

Health is an adaptive state unique to each person. This subjective state must be distinguished from the objective state of disease. The experience of health and illness (or poor health) can occur both in the absence and presence of objective disease. Given that the subjective experience of health, as well as the finding of objective disease in the community, follow a Pareto distribution, the following questions arise: What are the processes that allow the emergence of four observable states-(1) subjective health in the absence of objective disease, (2) subjective health in the presence of objective disease, (3) illness in the absence of objective disease, and (4) illness in the presence of objective disease? If we consider each individual as a unique biological system, these four health states must emerge from physiological network structures and personal behaviors. The underlying physiological mechanisms primarily arise from the dynamics of external environmental and internal patho/physiological stimuli, which activate regulatory systems including the hypothalamic-pituitary-adrenal axis and autonomic nervous system. Together with other systems, they enable feedback interactions between all of the person's system domains and impact on his system's entropy. These interactions affect individual behaviors, emotional, and cognitive responses, as well as molecular, cellular, and organ system level functions. This paper explores the hypothesis that health is an emergent state that arises from hierarchical network interactions between a person's external environment and internal physiology. As a result, the concept of health synthesizes available qualitative and quantitative evidence of interdependencies and constraints that indicate its top-down and bottom-up causative mechanisms. Thus, to provide effective care, we must use strategies that combine person-centeredness with the scientific approaches that address the molecular network physiology, which together underpin health and disease. Moreover, we propose that good health can also be promoted by strengthening resilience and self-efficacy at the personal and social level, and via cohesion at the population level. Understanding health as a state that is both individualized and that emerges from multi-scale interdependencies between microlevel physiological mechanisms of health and disease and macrolevel societal domains may provide the basis for a new public discourse for health service and health system redesign.

Resilience for health-an emergent property of the "health systems as a whole"

Resilience has become a popular term, and its meaning varies widely depending on the context of its use. Its Latin origin, resilire, means "bouncing back"-should bouncing back be understood literally or rather metaphorically in the context of health, illness, dis-ease, and disease? This essay examines ecological, physiological, personal, and health system perspectives inherent in the concept of resilience. It emerges that regardless of the level of aggregation, resilience is a systems property-it is as much a property of each of the subsystems of network physiology, the person, and the health care delivery system as it is a property of the health system as a whole. Given the interdependencies between people, their internal and external environments, and the health service system, strengthening resilience, ie, the ability to positively adapt to challenges and changing circumstances, will require a broad-based public discourse: "How can we strengthen resilience and health for the benefit of people and society at large".

Systems Medicine Disease: Disease Classification and Scalability Beyond Networks and Boundary Conditions

In order to accommodate the forthcoming wealth of health and disease related information, from genome to body sensors to population and the environment, the approach to disease description and definition demands re-examination. Traditional classification methods remain trapped by history; to provide the descriptive features that are required for a comprehensive description of disease, systems science, which realizes dynamic processes, adaptive response, and asynchronous communication channels, must be applied (Wolkenhauer et al., 2013). When Disease is viewed beyond the thresholds of lines and threshold boundaries, disease definition is not only the result of reductionist, mechanistic categories which reluctantly face re-composition. Disease is process and synergy as the characteristics of Systems Biology and Systems Medicine are included. To capture the wealth of information and contribute meaningfully to medical practice and biology research, Disease classification goes beyond a single spatial biologic level or static time assignment to include the interface of Disease process and organism response (Bechtel, 2017a; Green et al., 2017).

From quantum foundations to applications and back

Quantum non-locality has been an extremely fruitful subject of research, leading the scientific revolution towards quantum information science, in particular, to device-independent quantum information processing. We argue that the time is ripe to work on another basic problem in the foundations of quantum physics, the quantum measurement problem, which should produce good physics in theoretical, mathematical, experimental and applied physics. We briefly review how quantum non-locality contributed to physics (including some outstanding open problems) and suggest ways in which questions around macroscopic quantumness could equally contribute to all aspects of physics.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'.

How Organisms Gained Causal Independence and How It Might Be Quantified

Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence.

CONCLUSION

organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.

Black-boxing and cause-effect power

Reductionism assumes that causation in the physical world occurs at the micro level, excluding the emergence of macro-level causation. We challenge this reductionist assumption by employing a principled, well-defined measure of intrinsic cause-effect power–integrated information (Φ), and showing that, according to this measure, it is possible for a macro level to “beat” the micro level. Simple systems were evaluated for Φ across different spatial and temporal scales by systematically considering all possible black boxes. These are macro elements that consist of one or more micro elements over one or more micro updates. Cause-effect power was evaluated based on the inputs and outputs of the black boxes, ignoring the internal micro elements that support their input-output function. We show how black-box elements can have more common inputs and outputs than the corresponding micro elements, revealing the emergence of high-order mechanisms and joint constraints that are not apparent at the micro level. As a consequence, a macro, black-box system can have higher Φ than its micro constituents by having more mechanisms (higher composition) that are more interconnected (higher integration). We also show that, for a given micro system, one can identify local maxima of Φ across several spatiotemporal scales. The framework is demonstrated on a simple biological system, the Boolean network model of the fission-yeast cell-cycle, for which we identify stable local maxima during the course of its simulated biological function. These local maxima correspond to macro levels of organization at which emergent cause-effect properties of physical systems come into focus, and provide a natural vantage point for scientific inquiries.

We challenge the reductionist assumption by studying causal properties of physical systems across different spatiotemporal scales. The result is that–contrary to reductionist views–causal power can emerge at macro scales. Rather than relying on the traditional notion of coarse-grains (averages), we introduce the notion of functional black boxes that are defined based on their input-output relationship. Using a sequence of examples, our work demonstrates that black boxes are particularly well suited to capture the heterogeneous and specialized nature of components in biological systems. While the emergence of coarse-grained systems relies on increased specificity, black-boxing reveals the importance of structure and integration. Our framework is mathematically rigorous and fully general, hence applicable across many disciplines; it is particularly useful in objectively identifying informative perspectives on complex systems in the physical sciences.

Coarse-graining as a downward causation mechanism

Downward causation is the controversial idea that 'higher' levels of organization can causally influence behaviour at 'lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Elastic Multi-scale Mechanisms: Computation and Biological Evolution

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

Top-down models in biology: explanation and control of complex living systems above the molecular level

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering.

Anesthetic Neuroprotection in Experimental Stroke in Rodents: A Systematic Review and Meta-analysis

BACKGROUND

Patients undergoing endovascular therapy for acute ischemic stroke may require general anesthesia to undergo the procedure. At present, there is little clinical evidence to guide the choice of anesthetic in this acute setting. The clinical implications of experimental studies demonstrating anesthetic neuroprotection are poorly understood. Here, the authors evaluated the impact of anesthetic treatment on neurologic outcome in experimental stroke.

METHODS

Controlled studies of anesthetics in stroke using the filament occlusion model were identified in electronic databases up to December 15, 2015. The primary outcome measures, infarct volume, and neurologic deficit score were used to calculate the normalized mean difference for each comparison. Meta-analysis of normalized mean difference values provided estimates of neuroprotection and contributions of predefined factors: study quality, the timing of treatment, and the duration of ischemia.

RESULTS

In 80 retrieved publications anesthetic treatment reduced neurologic injury by 28% (95% CI, 24 to 32%; P < 0.0001). Internal validity was high: publication bias enhanced the effect size by 4% or less, effect size increased with study quality (P = 0.0004), and approximately 70% of studies were adequately powered. Apart from study quality, no predefined factor influenced neuroprotection. Neuroprotection failed in animals with comorbidities. Neuroprotection by anesthetics was associated with prosurvival mechanisms.

CONCLUSIONS

Anesthetic neuroprotection is a robust finding in studies using the filament occlusion model of ischemic stroke and should be assumed to influence outcomes in studies using this model. Neuroprotection failed in female animals and animals with comorbidities, suggesting that the results in young male animals may not reflect human stroke.